This study examines the alignment of deep learning model representations with those of humans, focusing on the typicality effect, where certain instances of a category are considered more representative than others. Previous research, limited to single modalities and few concepts, showed modest correlations with human typicality judgments. This study expands the scope by evaluating a wider array of language (N=8) and vision (N=10) models. It also considers the combined predictions of language+vision model pairs, alongside a multimodal CLIP-based model. The investigation encompasses a larger concept range (N=27) than prior work. Our findings reveal that language models align more closely with human typicality judgments than vision models. Additionally, combined language+vision models, as well as the multimodal CLIP model, demonstrate improved prediction of human typicality data. This study advances the understanding of ML models' conceptual alignment with human cognition and contributes a new image set for vision model concept evaluation.

When reading temporarily ambiguous garden-path sentences, misinterpretations sometimes linger past the point of disambiguation. This phenomenon has traditionally been studied in psycholinguistic experiments using online measures such as reading times and offline measures such as comprehension questions. Here, we investigate the processing of garden-path sentences and the fate of lingering misinterpretations using four large language models (LLMs): GPT-2, LLaMA-2, Flan-T5, and RoBERTa. The overall goal is to evaluate whether humans and LLMs are aligned in their processing of garden-path sentences and in the lingering misinterpretations past the point of disambiguation, especially when extra-syntactic information (e.g., a comma delimiting a clause boundary) is present to guide processing. We address this goal using 24 garden-path sentences that have optional transitive and reflexive verbs leading to temporary ambiguities. For each sentence, there are a pair of comprehension questions corresponding to the misinterpretation and the correct interpretation. In three experiments, we (1) measure the dynamic semantic interpretations of LLMs using the question-answering task; (2) track whether these models shift their implicit parse tree at the point of disambiguation (or by the end of the sentence); and (3) visualize the model components that attend to disambiguating information when processing the question probes. These experiments show promising alignment between humans and LLMs in the processing of garden-path sentences, especially when extra-syntactic information is available to guide processing.

Although declines in cognitive capacity are assumed to be a characteristic of aging, increasing evidence shows that it is age-related disease, rather than age itself, that causes cognitive impairment. Even so, older age is a primary risk factor for cognitive decline, and with individuals living longer as a result of medical advances, cognitive impairment and dementia are increasing in prevalence. On March 26 to 27, 2018, the American Geriatrics Society convened a conference in Bethesda, MD, to explore cognitive impairment across the subspecialties. Bringing together representatives from several subspecialties, this was the third of three conferences, supported by a U13 grant from the National Institute on Aging, to aid recipients of Grants for Early Medical/Surgical Specialists Transition to Aging Research (GEMSSTAR) in integrating geriatrics into their subspecialties. Scientific sessions focused on the impact of cognitive impairment, sensory contributors, comorbidities, links between delirium and dementia, and issues of informed consent in cognitively impaired populations. Discussions highlighted the complexity not only of cognitive health itself, but also of the bidirectional relationship between cognitive health and the health of other organ systems. Thus, conference participants noted the importance of multidisciplinary team science in future aging research. This article summarizes the full conference report, The Impact of Cognitive Impairment Across Specialties, and notes areas where GEMSSTAR scholars can contribute to progress as they embark on their careers in aging research. J Am Geriatr Soc 67:2011-2017, 2019.

Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6-77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people.Trial registration Clinicaltrials.gov (NCT01038583).

Introduction

Racial and ethnic groups are under-represented among research subjects who assent to brain donation in Alzheimer disease research studies. There has been little research on this important topic. Although there are some studies that have investigated the barriers to brain donation among African American study volunteers, there is no known research on the factors that influence whether or not Asians or Latinos are willing to donate their brains for research.

Methods

African American, Caucasian, Asian, and Latino research volunteers were surveyed at 15 Alzheimer Disease Centers to identify predictors of willingness to assent to brain donation.

Results

Positive predictors included older age, Latino ethnicity, understanding of how the brain is used by researchers, and understanding of what participants need to do to ensure that their brain will be donated. Negative predictors included African/African American race, belief that the body should remain whole at burial, and concern that researchers might not be respectful of the body during autopsy.

Discussion

The predictive factors identified in this study may be useful for researchers seeking to increase participation of diverse ethnic groups in brain donation.

Although declines in cognitive capacity are assumed to be a characteristic of aging, increasing evidence shows that it is age-related disease, rather than age itself, that causes cognitive impairment. Even so, older age is a primary risk factor for cognitive decline, and with individuals living longer as a result of medical advances, cognitive impairment and dementia are increasing in prevalence. On March 26 to 27, 2018, the American Geriatrics Society convened a conference in Bethesda, MD, to explore cognitive impairment across the subspecialties. Bringing together representatives from several subspecialties, this was the third of three conferences, supported by a U13 grant from the National Institute on Aging, to aid recipients of Grants for Early Medical/Surgical Specialists' Transition to Aging Research (GEMSSTAR) in integrating geriatrics into their subspecialties. Scientific sessions focused on the impact of cognitive impairment, sensory contributors, comorbidities, links between delirium and dementia, and issues of informed consent in cognitively impaired populations. Discussions highlighted the complexity not only of cognitive health itself, but also of the bidirectional relationship between cognitive health and the health of other organ systems. Thus, conference participants noted the importance of multidisciplinary team science in future aging research. This article summarizes the full conference report, "The Impact of Cognitive Impairment Across Specialties," and notes areas where GEMSSTAR scholars can contribute to progress as they embark on their careers in aging research. J Am Geriatr Soc 67:2011-2017, 2019.

Worldwide, over 35 million people suffer from Alzheimer's disease and related dementias. This number is expected to triple over the next 40 years. How can we improve the evidence supporting strategies to reduce the rate of dementia in future generations? The risk of dementia is likely influenced by modifiable factors such as exercise, cognitive activity, and the clinical management of diabetes and hypertension. However, the quality of evidence is limited and it remains unclear whether specific interventions to reduce these modifiable risk factors can, in turn, reduce the risk of dementia. Although randomized controlled trials are the gold-standard for causality, the majority of evidence for long-term dementia prevention derives from, and will likely continue to derive from, observational studies. Although observational research has some unavoidable limitations, its utility for dementia prevention might be improved by, for example, better distinction between confirmatory and exploratory research, higher reporting standards, investment in effectiveness research enabled by increased data-pooling, and standardized exposure and outcome measures. Informed decision-making by the general public on low-risk health choices that could have broad potential benefits could be enabled by internet-based tools and decision-aids to communicate the evidence, its quality, and the estimated magnitude of effect.

Introduction

The NIH All of Us Research Program will have the scale and scope to enable research for a wide range of diseases, including cancer. The program's focus on diversity and inclusion promises a better understanding of the unequal burden of cancer. Preliminary cancer ascertainment in the All of Us cohort from two data sources (self-reported versus electronic health records (EHR)) is considered.

Materials and methods

This work was performed on data collected from the All of Us Research Program's 315,297 enrolled participants to date using the Researcher Workbench, where approved researchers can access and analyze All of Us data on cancer and other diseases. Cancer case ascertainment was performed using data from EHR and self-reported surveys across key factors. Distribution of cancer types and concordance of data sources by cancer site and demographics is analyzed.

Results and discussion

Data collected from 315,297 participants resulted in 13,298 cancer cases detected in the survey (in 89,261 participants), 23,520 cancer cases detected in the EHR (in 203,813 participants), and 7,123 cancer cases detected across both sources (in 62,497 participants). Key differences in survey completion by race/ethnicity impacted the makeup of cohorts when compared to cancer in the EHR and national NCI SEER data.

Conclusions

This study provides key insight into cancer detection in the All of Us Research Program and points to the existing strengths and limitations of All of Us as a platform for cancer research now and in the future.

Background

Probe-based confocal laser endomicroscopy (pCLE) provides microscopic imaging during an endoscopic procedure. Its introduction as a standard modality in gastroenterology has brought significant progress in management strategies, affecting many aspects of clinical care and requiring standardisation of practice and training.

Objective

This study aimed to provide guidance on the standardisation of its practice and training in Barrett's oesophagus, biliary strictures, colorectal lesions and inflammatory bowel diseases.

Methods

Initial statements were developed by five group leaders, based on the available clinical evidence. These statements were then voted and edited by the 26 participants, using a modified Delphi approach. After two rounds of votes, statements were validated if the threshold of agreement was higher than 75%.

Results

Twenty-six experts participated and, among a total of 77 statements, 61 were adopted (79%) and 16 were rejected (21%). The adoption of each statement was justified by the grade of evidence.

Conclusion

pCLE should be used to enhance the diagnostic arsenal in the evaluation of these indications, by providing microscopic information which improves the diagnostic performance of the physician. In order actually to implement this technology in the clinical routine, and to ensure good practice, standardised initial and continuing institutional training programmes should be established.